Performance Limits of Stochastic Sub-Gradient Learning, Part I: Single Agent Case

24 Nov 2015Bicheng YingAli H. Sayed

In this work and the supporting Part II, we examine the performance of stochastic sub-gradient learning strategies under weaker conditions than usually considered in the literature. The new conditions are shown to be automatically satisfied by several important cases of interest including SVM, LASSO, and Total-Variation denoising formulations... (read more)

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